Big Data for Remote Sensing: Visualization, Analysis and Interpretation, Softcover reprint of the original 1st ed. 2019 Digital Earth and Smart Earth
Coordonnateurs : Dey Nilanjan, Bhatt Chintan, Ashour Amira S.
This book thoroughly covers the remote sensing visualization and analysis techniques based on computational imaging and vision in Earth science.
Remote sensing is considered a significant information source for monitoring and mapping natural and man-made land through the development of sensor resolutions that committed different Earth observation platforms. The book includes related topics for the different systems, models, and approaches used in the visualization of remote sensing images. It offers flexible and sophisticated solutions for removing uncertainty from the satellite data. It introduces real time big data analytics to derive intelligence systems in enterprise earth science applications. Furthermore, the book integrates statistical concepts with computer-based geographic information systems (GIS). It focuses on image processing techniques for observing data together with uncertainty information raised by spectral, spatial, and positional accuracy of GPS data. The book addresses several advanced improvement models to guide the engineers in developing different remote sensing visualization and analysis schemes. Highlights on the advanced improvement models of the supervised/unsupervised classification algorithms, support vector machines, artificial neural networks, fuzzy logic, decision-making algorithms, and Time Series Model and Forecasting are addressed.
This book guides engineers, designers, and researchers to exploit the intrinsic design remote sensing systems. The book gathers remarkable material from an international experts' panel to guide the readers during the development of earth big data analytics and their challenges.
Nilanjan Dey is an Assistant Professor at the Department of Information Technology, Techno India College of Technology, Kolkata, W.B., India. He holds an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA and Research Scientist of Laboratory of Applied Mathematical Modeling in Human Physiology, Territorial Organization of- Scientific and Engineering Unions, BULGARIA. Associate Researcher of Laboratoire RIADI, University of Manouba, TUNISIA. His research topic is Medical Imaging, Soft computing, Data mining, Machine learning, Rough set, Computer Aided Diagnosis, Atherosclerosis. He has 20 books and 300 international conferences and journal papers. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence (IGI Global), US, International Journal of Rough Sets and Data Analysis (IGI Global), US, the International Journal of Synthetic Emotions (IJSE), IGI Global, US, and International Journal of Natural Computing Research (IGI Global), US. Series Editor of Advances in Geospatial Technologies (AGT) Book Series, (IGI Global), US, Executive Editor of International Journal of Image Mining (IJIM), Inderscience, and Associated Editor of IEEE Access journal and the International Journal of Service Science, Management, Engineering and Technology, IGI Global. He is a life member of IE, UACEE, ISOC
Chintan Bhatt is an Assistant Professor of U & P U Patel Department of Computer Engineering at Charotar University of Science And Technology. His PhD in Computer Science, he was M.Tech. in Computer Engineering, Dharmsinh Desai University, 2009 - 2011, B.E. in Computer Engineering, Gujarat University (Charotar Institute of Technology), 2005 – 2009. His research interests include Data Mining, Software Engineering, Networking, Big Data, Internet of Things (IoT), Mobile Computing. He received an award on 2015, Paper Publication at International Conference Award and Faculty with Maximum Pu
Addresses the remote sensing and big data techniques/challenges along with up-to-date related topics
Discusses advanced synthetic aperture radar imaging and feature analysis to detect images of a moving target in SAR
Covers several studies on geocoding for airborne SAR image based on the global position system (GPS)
Presents different applications of the remote sensing big data analysis and visualization
Involves several digital earth applications to recognize the natural disasters impacts/city buildings distribution changing over time
Guides the designers/researchers to exploit the inherent advantages of visualization and analysis of the remote sensing technology
Date de parution : 12-2018
Ouvrage de 154 p.
15.5x23.5 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 158,24 €
Ajouter au panierDate de parution : 06-2018
Ouvrage de 154 p.
15.5x23.5 cm
Thème de Big Data for Remote Sensing: Visualization, Analysis and... :
Mots-clés :
Earth Science; Big Data Analytics; Remote Sensing; Synthetic Aperture Radar (SAR); Location of Air-borne SAR Imagery; Machine Learning Based Earth Data Analysis and Processing; Statistical Earth and Environmental Data Analysis; Big Data for Remote Sensing Visualization and Analysis; Earth Imaging; Earth Data Analysis; uncertainty processing; remote sensing visualization scheme